scholarly journals The curious case of apparent resistance of Shaheen Bagh protesters to COVID-19 pandemic

2020 ◽  
Author(s):  
Hari Mohan Saxena

The Shaheen Bagh protest, an ongoing continuous sit-in protest by several hundred people in Shaheen Bagh area of New Delhi since 15 December 2019, is a curious case where not a single person with COVID-19 infection has been found yet since the beginning of the pandemic engulfing the entire globe. Possible explanations for this resistance to the virus could be the innate immunity in the local population and Herd immunity generated by the resistant individuals could also protect the small numbers of other protesters who are not immune. This needs further investigation. The innate immunity and herd immunity in the indigenous population should be taken into consideration while devising global public health strategies for control of pandemics and epidemics.

2019 ◽  
Vol 64 (3) ◽  
Author(s):  
Steven R. Torres ◽  
Amber Pichowicz ◽  
Fernando Torres-Velez ◽  
Renjie Song ◽  
Navjot Singh ◽  
...  

ABSTRACT Candida auris has become a global public health threat due to its multidrug resistance and persistence. Currently, there are limited murine models to study C. auris infection. Those models use a combination of cyclophosphamide and cortisone acetate, suppressing both innate and adaptive immunity. Here, we compare C. auris infection in two neutrophil-depleted murine models in which innate immunity is targeted using the monoclonal antibodies 1A8 and RB6-8C5.


2021 ◽  
Author(s):  
Qian Niu ◽  
Junyu Liu ◽  
Masaya Kato ◽  
Yuki Shinohara ◽  
Natsuki Matsumura ◽  
...  

BACKGROUND The global public health and socioeconomic impacts of COVID-19 have been substantial. To achieve herd immunity, widespread use of the vaccine is required, and it is therefore critical for government and public health agencies to understand public perceptions of the vaccine to help sustain subsequent vaccinations. OBJECTIVE This study aims to explore the opinions and sentiments of tweets about COVID-19 vaccination among Twitter users in Japan, both before and at the beginning of the COVID-19 vaccination program. METHODS We collected 144,101 Japanese tweets containing COVID-19 vaccine-related keywords from Japanese Twitter users between August 1, 2020, and June 30, 2021. Specifically, we identified temporal changes in the number of tweets and key events that triggered a surge in the number of tweets. In addition, we performed sentiment analysis, and calculated the correlation between different sentiments and the number of deaths, infections, and vaccinations. We also built latent Dirichlet allocation (LDA) topic models to identify commonly discussed topics in a large sample of tweets. We also provided a word cloud of high-frequency unigram and bigram tokens as additional evidence, and conducted further analysis on three different vaccine brands. RESULTS The overall number of tweets has continued to increase since the start of mass vaccination in Japan. Sentiments were generally neutral, but negative sentiment was more significant than positive sentiment. Before and after the first vaccination in Japan, the correlations of negative/positive sentiment with death, infection, and vaccination cases changed significantly. Public concerns revolved around three themes: information on vaccine reservations and vaccinations in Japan; infection and mutation of COVID-19 in Japan; and prevention measures, vaccine development and supply, and vaccination status in other countries. Furthermore, public attention to the three brands of vaccines has a temporal shift as clinical trials move forward. CONCLUSIONS The number of tweets and changes in sentiment might be driven by major news events in relation to the COVID-19 vaccine, with negative sentiments dominating positive sentiments overall. Death and infection cases correlated significantly with negative sentiments, but the correlation fell after vaccinations began as morbidity and mortality decreased. The public’s attention to different vaccine brands had a temporal change during their clinical trial process, and although the discussion points are slightly different, the core remains effective and secure.


2020 ◽  
Vol 71 (10) ◽  
pp. 2752-2756 ◽  
Author(s):  
Hanalise V Huff ◽  
Avantika Singh

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly in a few months despite global public health strategies to curb transmission by testing symptomatic patients and social distancing. This review summarizes evidence that highlights transmission by asymptomatic and presymptomatic individuals. Viral load of asymptomatic and symptomatic cases is comparable. Viral shedding is highest before symptom onset, suggesting high transmissibility before symptoms. Within universally tested subgroups, high percentages of SARS-CoV-2 infected asymptomatic individuals were found. Asymptomatic transmission was reported in several clusters, including a Wuhan study showing an alarming rate of intrahospital transmission. Several countries reported higher prevalence among healthcare workers than general population raising concern that healthcare workers could act as silent vectors. Therefore, current strategies that rely solely on “symptom onset” for infection identification need urgent reassessment. Extensive universal testing irrespective of symptoms may be considered, with priority placed on groups with high frequency exposure to positive patients.


eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
José Lourenço ◽  
Maricelia Maia de Lima ◽  
Nuno Rodrigues Faria ◽  
Andrew Walker ◽  
Moritz UG Kraemer ◽  
...  

The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting.


2017 ◽  
Vol 31 (2) ◽  
pp. 138 ◽  
Author(s):  
SaurabhRamBihariLal Shrivastava ◽  
PrateekSaurabh Shrivastava ◽  
Jegadeesh Ramasamy

2020 ◽  
Vol 9 (3) ◽  
pp. 11-15
Author(s):  
Abu Sadat Mohammad Nurunnabi ◽  
Miliva Mozaffor ◽  
Mohammad Akram Hossain ◽  
Sadia Akther Sony

Vaccines are responsible for many global public health successes, such as the eradication of smallpox and significant reductions in other serious infections like diphtheria, pertussis, tetanus, polio and measles. However, mass vaccination has also been the subject of various ethical controversies for decades. Several factors need to be considered before any vaccine is deployed at national programme like the potential burden of disease in the country or region, the duration of the protection conferred, herd immunity in addition to individual protection, vaccine-related risks, financing and the logistical feasibility of the large-scale vaccination. Moreover, several ethical dilemmas revolve around authority and mandates for vaccination, informed consent, benefits vs. risks, and disparities in access to vaccination. This review paper aims to elaborate the ethical issues involved in mass vaccination programme and present some additional challenges in the context of a resource-poor settings of public health in Bangladesh.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251550
Author(s):  
Gloria Hyunjung Kwak ◽  
Lowell Ling ◽  
Pan Hui

Background Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic to control the spread of SARS-CoV-2 virus. It is a challenge to implement timely and appropriate public health interventions. Methods and findings Population and COVID-19 epidemiological data between 21st January 2020 to 15th November 2020 from 216 countries and territories were included with the implemented public health interventions. We used deep reinforcement learning, and the algorithm was trained to enable agents to try to find optimal public health strategies that maximized total reward on controlling the spread of COVID-19. The results suggested by the algorithm were analyzed against the actual timing and intensity of lockdown and travel restrictions. Early implementations of the actual lockdown and travel restriction policies, usually at the time of local index case were associated with less burden of COVID-19. In contrast, our agent suggested to initiate at least minimal intensity of lockdown or travel restriction even before or on the day of the index case in each country and territory. In addition, the agent mostly recommended a combination of lockdown and travel restrictions and higher intensity policies than the policies implemented by governments, but did not always encourage rapid full lockdown and full border closures. The limitation of this study was that it was done with incomplete data due to the emerging COVID-19 epidemic, inconsistent testing and reporting. In addition, our research focuses only on population health benefits by controlling the spread of COVID-19 without balancing the negative impacts of economic and social consequences. Interpretation Compared to actual government implementation, our algorithm mostly recommended earlier intensity of lockdown and travel restrictions. Reinforcement learning may be used as a decision support tool for implementation of public health interventions during COVID-19 and future pandemics.


2020 ◽  
Author(s):  
Kwak Gloria Hyunjung ◽  
Lowell Ling ◽  
Pan Hui

Abstract Rationale: Unprecedented public health measures have been used during this coronavirus 2019 (COVID-19) pandemic but with a cost to economic and social disruption. It is a challenge to implement timely and appropriate public health interventions.Objectives: This study evaluates the timing and intensity of public health policies in each country and territory in the COVID-19 pandemic, and whether machine learning can help them to find better global health strategies.Methods: Population and COVID-19 epidemiological data between 21st January 2020 to 7th April 2020 from 183 countries and 78 territories were included with the implemented public health interventions. We used deep reinforcement learning, and the model was trained to try to find the optimal public health strategies with maximizing total reward on controlling spread of COVID-19. The results proposed by the model were analyzed against the actual timing and intensity of lockdown and travel restrictions.Measurements and Main Results: Early implementation of the actual lockdown and travel restriction policies were associated with gradually groups of less severe crisis severity, relative to local index case date in each country or territory, not to 31st December 2019. However, our model suggested to initiate at least minimal intensity of lockdown or travel restriction even before index cases in each country and territory. In addition, the model mostly recommended a combination of lockdown and travel restrictions and higher intensity policies than the implemented policies by government, but did not always encourage rapid full lockdown and full border closures.Conclusion: Compared to actual government implementation, our model mostly recommended earlier and higher intensity of lockdown and travel restrictions. Machine learning may be used as a decision support tool for implementation of public health interventions during COVID-19 and future pandemics.


2021 ◽  
Vol 46 (4) ◽  
pp. 2-4
Author(s):  
Nicanor Pier Giorgio Austriaco ◽  

Although COVID-19 vaccine credentials for international travel are an unwelcome or dangerous concept to some in the developed world, such measures are an essential component of global public health in some of the poorest countries of the world, in particular to prevent the spread of yellow fever. If one accepts the liceity of vaccine credentials for yellow fever in the developing world, then one has to do the same with similar credentials for COVID-19. A COVID-19 vaccine credential will allow developing countries to reopen their borders and economies long before they can attain herd immunity. It will be a lifeline for economies that have been ravaged by the global pandemic. It will be part of the global common good.


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